High entropy photocatalysts for energy and environmental applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Today, the energy and environmental crisis originating from the use of fossil fuels and carbon dioxide (CO2) emissions has become a common concern in lives of people. Photocatalysis is a promising clean technology receiving much attention. There are diverse strategies to enhance the efficiency of photocatalysis, and high entropy photocatalysts (HEPs) show great potential as new efficient photocatalysts. The tunability of HEPs provides more possibilities for the design of the electronic structure of the catalysts, which leads to the efficient separation of electron-hole pairs and substantially enhances the photocatalytic performance. This review discusses the composition of HEPs, their advantages in photocatalysis, characterization, and prediction, and the latest applications of various photocatalytic systems. Finally, we discuss and summarize the challenges and the prospects of HEPs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it